Xingjian Bai is a final-year undergraduate student at Oxford. He has been advised by Prof. Jan Obloj, Prof. Christian Coester, Prof. Christian Rupprecht, and Luke Melas-Kyriazi. His research interest lies in theory-inspired machine learning and learning-augmented classic algorithms.


  • Xingjian Bai and Christian Coester. Sorting with Predictions. NeurIPS 2023. [arXiv]
  • Xingjian Bai, Guangyi He, Yifan Jiang, and Jan Obloj. Wasserstein Distributional Robustness of Neural Networks. NeurIPS 2023. [arXiv]
  • Xingjian Bai and Luke Melas-Kyriazi. Fixed Point Diffusion Models. Under review at CVPR 2024. [arXiv]
  • Jacek Karwowski, Oliver Hayman, Xingjian Bai, Klaus Kiendlhofer, Charlie Griffin, and Joar Skalse. Goodhart’s Law in Reinforcement Learning. ICLR 2024. [arXiv] [Post]
  • Xingjian Bai, Ruining Ma, and Yulong Lou. Containing Invasive Species via Cellular Automaton and AI. Journal of Undergraduate Mathematics and Its Applications (UMAP), 2021. American Mathematics Society Best Paper Award.
  • Hannah Rose Kirk, Yennie Jun, Paulius Rauba, Gal Wachtel, Ruining Li, Xingjian Bai, Noah Broestl, Martin Doff-Sotta, Aleksandar Shtedritski, Yuki M. Asano. Memes in the Wild: Assessing the Generalizability of the Hateful Memes Challenge Dataset. Proceedings of the 5th Workshop on Online Abuse and Harms, 2021. [arXiv]


  • NeurIPS Scholar Award 2023
  • European Regional Gold Medalist, advancing to World Final 2023 - The ICPC International Collegiate Programing Contest
  • Outstanding Winner & American Mathematics Society Best Paper (the top out of 10053 entries) - 37th Mathematical Contest in Modeling
  • “Hack the Hackers’ Hack” award, best out of 66 teams - Oxford Hackathon 2020
  • Full Score - USA Computing Olympiad Open 2019
  • First place in national team selection - Canadian Computing Olympiad 2018
  • Silver Medalist - Chinese National Olympiad in Informatics 2018